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Record W4392918529 · doi:10.47191/ijcsrr/v7-i3-33

Pathological Study of Rare Case of Duodenal Leiomyosarcoma in a Labrador Dog

2024· article· en· W4392918529 on OpenAlexaboutno aff
Prashant Sonkusale, U. P. Mainde, S. Chaitanya, Samiksha Suroshe

Bibliographic record

VenueInternational Journal of Current Science Research and Review · 2024
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Tumor Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsLeiomyosarcomaDuodenumMelenaLumen (anatomy)AnatomyPathologyPathologicalMedicineSmooth muscleInternal medicine

Abstract

fetched live from OpenAlex

The leiomyosarcoma is a tumor of mesenchymal origin of smooth, malignant, slow-growing muscles. The present study reports a case of duodenal leiomyosarcoma in Labrador dog. A 6 year old black female Labrador dog with history off feed, vomition and melena brought for necropsy examination. Gross lesions revealed tennis ball size tumorus mass at the initial portion of duodenum resulting into the obstruction of intestinal lumen. Microscopically, duodenum with tumours mass revealed smooth muscle bundles arranged in all the directions having elongated blunt ended nuclei along with numerous blood vessels and mitotic figure which is indicative of leiomyosarcoma.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.182
GPT teacher head0.540
Teacher spread0.358 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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